In [11]:
#importing necessary modules 
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import plotly.express as px
import seaborn as sns
import copairs
import pycytominer
from copairs.map import average_precision
from copairs.map import mean_average_precision
from utils import * 

%load_ext autoreload
%autoreload 2

The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

Reading the dataframes¶

In [3]:
#Reading the normalized and feature selected files for copairs - fixed cells and 48h time point
dict_to_load_feature_selected = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122250_normalized_feature_select_negcon_batch.csv':'Standard CP',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122246_normalized_feature_select_negcon_batch.csv':'CP + MitoBrilliant',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122247_normalized_feature_select_negcon_batch.csv':'CP + Phenovue phalloidin 400LS',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122248_normalized_feature_select_negcon_batch.csv':'Standard CP (exposed to ChromaLive)',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122249_normalized_feature_select_negcon_batch_wo_phasefeatures.csv':'ChromaLive + Hoechst'

}

Phenotypic Activity¶

In [4]:
### Copairs on standard feature selected batches - mAP with respect to controls
mAP_control_plot, mAP_control_dict = copairs_batches_newerversion(dict_to_load_feature_selected, mAP='Control')
In [34]:
mAP_control_plot.show('notebook')

mAP based on MoA¶

Reading the result csv of copairs to get add the cell count info¶

In [5]:
result_csv ={'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122250_normalized_feature_select_negcon_batch_Result_NegconNorm_mAP_wrt_Control_woNAN.csv':'Standard CP', 
             'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122246_normalized_feature_select_negcon_batch_Result_NegconNorm_mAP_wrt_Control_woNAN.csv':'CP + MitoBrilliant',
            'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122247_normalized_feature_select_negcon_batch_Result_NegconNorm_mAP_wrt_Control_woNAN.csv':'CP + Phenovue phalloidin 400LS',
            'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122248_normalized_feature_select_negcon_batch_Result_NegconNorm_mAP_wrt_Control_woNAN.csv':'Standard CP (exposed to ChromaLive)',
            'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122249_normalized_feature_select_negcon_batch_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Control_woNAN.csv':'ChromaLive + Hoechst'}

Reading the aggregate csv files of copairs¶

In [6]:
aggregate_files_dict = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122250_normalized_feature_select_negcon_batch_Aggregate_result_NegconNorm_mAP_wrt_Control_woNAN.csv':'Standard CP',
                        'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122246_normalized_feature_select_negcon_batch_Aggregate_result_NegconNorm_mAP_wrt_Control_woNAN.csv':'CP + MitoBrilliant',
                        'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122247_normalized_feature_select_negcon_batch_Aggregate_result_NegconNorm_mAP_wrt_Control_woNAN.csv':'CP + Phenovue phalloidin 400LS',
                        'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122248_normalized_feature_select_negcon_batch_Aggregate_result_NegconNorm_mAP_wrt_Control_woNAN.csv':'Standard CP (exposed to ChromaLive)',
                        'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122249_normalized_feature_select_negcon_batch_wo_phasefeatures_Aggregate_result_NegconNorm_mAP_wrt_Control_woNAN.csv':'ChromaLive + Hoechst'}

Plot generation¶

In [9]:
moA_control_plot, df_controls = cell_count_norm_colorscheme(result_csv, aggregate_files_dict)
In [35]:
moA_control_plot.show('notebook')

Phenotypic Distinctiveness¶

In [17]:
mAP_treatment_plot, mAP_treatment_dict = copairs_batches_newerversion(dict_to_load_feature_selected, mAP='Treatment')
In [36]:
mAP_treatment_plot.show('notebook')

mAP based on MoA¶

Reading the result csv of copairs to get add the cell count info¶

In [13]:
#Reading the result CSVs obtained from the copairs 
result_csv_trmts = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122250_normalized_feature_select_negcon_batch_Result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'Standard CP',
                    'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122246_normalized_feature_select_negcon_batch_Result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'CP + MitoBrilliant',
                    'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122247_normalized_feature_select_negcon_batch_Result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'CP + Phenovue phalloidin 400LS',
                    'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122248_normalized_feature_select_negcon_batch_Result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'Standard CP (exposed to ChromaLive)',
                    'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122249_normalized_feature_select_negcon_batch_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'ChromaLive + Hoechst'}

Reading the aggregate csv files of copairs¶

In [14]:
#Reading the aggregate CSV files obtained from the copairs package
aggregate_files_trmt = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122250_normalized_feature_select_negcon_batch_Aggregate_result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'Standard CP',
                    'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122246_normalized_feature_select_negcon_batch_Aggregate_result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'CP + MitoBrilliant',
                    'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122247_normalized_feature_select_negcon_batch_Aggregate_result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'CP + Phenovue phalloidin 400LS',
                    'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122248_normalized_feature_select_negcon_batch_Aggregate_result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'Standard CP (exposed to ChromaLive)',
                    'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\BR00122249_normalized_feature_select_negcon_batch_wo_phasefeatures_Aggregate_result_NegconNorm_mAP_wrt_Treatment_woNAN.csv':'ChromaLive + Hoechst'}

Plot generation¶

In [15]:
mAP_treatment_plot_colorscheme, df_treatment = cell_count_norm_colorscheme(result_csv_trmts, aggregate_files_trmt)
In [16]:
mAP_treatment_plot_colorscheme.update_layout(legend=dict(x=0,y=1,xanchor='left',yanchor='top'))
In [37]:
mAP_treatment_plot_colorscheme.show('notebook')

Phenotypic Activity - Early Time Point¶

In [18]:
dict_to_load_feature_selected_early_timepoint_48h = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_normalized_negcon_wo_phasefeatures.csv':'ChromaLive+DRAQ7+Cas3/7_4h',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_24h_normalized_negcon_wo_phasefeatures.csv':'ChromaLive+DRAQ7+Cas3/7_24h',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures.csv':'ChromaLive_4h',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures.csv':'ChromaLive_24h',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures.csv':'ChromaLive_48h'
}
In [19]:
mAP_earlytimepoint_plot_48h, mAP_earlytimepoint_dict_48h = copairs_batches_earlytimepoint(dict_to_load_feature_selected_early_timepoint_48h, mAP='Control')
In [38]:
mAP_earlytimepoint_plot_48h.show('notebook')

mAP based on MoA¶

mAP with respect to Controls - MoA¶

Reading the result csv of copairs to get add the cell count info¶

In [20]:
earlytime_point_result_csv = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive+DRAQ7+Cas3/7_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_24h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive+DRAQ7+Cas3/7_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_48h'

}
In [21]:
earlytime_point_aggregate_csv = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive+DRAQ7+Cas3/7_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_24h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive+DRAQ7+Cas3/7_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures_Aggregate_result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_48h'

}
In [22]:
moA_control_earlytime_point_plot, df_earlytime_point_controls = cell_count_norm_colorscheme_early(earlytime_point_result_csv,earlytime_point_aggregate_csv)
In [23]:
earlytime_point_result_csv_part2 ={'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_48h'}
In [24]:
earlytime_point_aggregate_csv_part2 = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures_Aggregate_result_NegconNorm_mAP_wrt_Control.csv':'ChromaLive_48h'}
In [25]:
moA_control_earlytime_point_plot_part2, df_earlytime_point_controls_part2 = cell_count_norm_colorscheme_early_part2(earlytime_point_result_csv_part2,earlytime_point_aggregate_csv_part2)

Phenotypic Distinctiveness - Early Time Point¶

In [26]:
dict_to_load_feature_selected_early_timepoint_48h = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_normalized_negcon_wo_phasefeatures.csv':'ChromaLive+DRAQ7+Cas3/7_4h',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_24h_normalized_negcon_wo_phasefeatures.csv':'ChromaLive+DRAQ7+Cas3/7_24h',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures.csv':'ChromaLive_4h',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures.csv':'ChromaLive_24h',
                                 'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures.csv':'ChromaLive_48h'
}
In [27]:
mAP_earlytimepoint_trmt_plot_48h, mAP_earlytimepoint_trmt_dict_48h = copairs_batches_earlytimepoint(dict_to_load_feature_selected_early_timepoint_48h, mAP='Treatment')
In [39]:
mAP_earlytimepoint_trmt_plot_48h.show('notebook')

mAP based on MoA¶

Reading the result csv of copairs to get add the cell count info¶

In [28]:
earlytime_point_result_csv_trmt = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive+DRAQ7+Cas3/7_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_24h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive+DRAQ7+Cas3/7_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_48h'

}
In [29]:
earlytime_point_aggregate_csv_trmt = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive+DRAQ7+Cas3/7_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122248_24h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive+DRAQ7+Cas3/7_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures_Aggregate_result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_48h'

}
In [30]:
moA_treatment_earlytime_point_plot, df_earlytime_point_treatment = cell_count_norm_colorscheme_early(earlytime_point_result_csv_trmt,earlytime_point_aggregate_csv_trmt)
In [31]:
earlytime_point_result_csv_trmt_part2   = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_48h'

}
In [32]:
earlytime_point_aggregate_csv_trmt_part2 = {'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_4h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_4h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\BR00122249_24h_normalized_negcon_wo_phasefeatures_Aggregate_Result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_24h',
                              'c:\\Users\\ssivagur\\Documents\\Projects\\Cell_painting_projects\\CDoT\\Batch3_analysis_redo\\UpdatedCopairsVersion\\EarlyTimePointProfiles\\saguaro_48h_fixedcell_data_normalized_negcon_wo_phasefeatures_wo_DNAfeatures_Aggregate_result_NegconNorm_mAP_wrt_Treatment.csv':'ChromaLive_48h'

}
In [33]:
moA_treatment_earlytime_point_plot_part2, df_earlytime_point_treatment_part2 = cell_count_norm_colorscheme_early_part2(earlytime_point_result_csv_trmt_part2,earlytime_point_aggregate_csv_trmt_part2)